2379 Courses in Glasgow delivered Online

Duration 4 Days 24 CPD hours This course is intended for This course is for people who have on the job experience doing project management activities and running projects, regardless of their job title. It is for those who wish to become certified project managers, or those that want to build or reinforce a foundation in project management. This course is ideal for a person who wants to grow and formalize their project management skills on an industry neutral, global standard, the Project Management Institute. Overview After completing this course, students will be able to: Demonstrate an understanding of the various project life cycles and processes. Distinguish between predictive and adaptive approaches. Demonstrate an understanding of project management planning. Demonstrate an understanding of project roles and responsibilities. Explain the importance of the role the project manager plays. Determine how to follow and execute and respond to planned strategies or frameworks (e.g., communication, risks, etc.). Demonstrate an understanding of common problem-solving tools and techniques. Identify the suitability of a predictive, plan-based approach for the organizational structure (e.g., virtual, colocation, matrix structure, hierarchical, etc.). Determine and give examples of the activities within each process. Demonstrate an understanding of a project management plan schedule. Determine how to document project controls of predictive, plan-based projects. Explain when it is appropriate and sustainable to use an adaptive approach for the organizational structure. Compare the pros and cons of adaptive and predictive, plan-based projects. Identify the suitability of adaptive approaches for the organizational structure (e.g., virtual, colocation, matrix structure, hierarchical, etc.). Identify organizational process assets and environmental factors that facilitate the use of adaptive approaches. Determine how to plan project iterations. Determine how to document project controls for an adaptive project. Distinguish between the components of different adaptive methodologies (e.g., Scrum, Extreme Programming (XP), Scaled Adaptive Framework (SAFe), Kanban, etc.). Determine how to prepare and execute task management steps. Demonstrate an understanding of business analysis (BA) roles and responsibilities. Demonstrate the importance of communication for a business analyst between various teams and stakeholders. Determine how to gather requirements and using the best approach for a situation. Explain the application of a product roadmap. Determine how project methodologies influence business analysis processes. Validate requirements through product delivery. Every career in project management has a beginning and that is the purpose of this course. You will learn the fundamentals of project management. This includes project performance, when to use the predictive or adaptive methodologies, business analysis domains, and frameworks, as well as the proper use of one of the various adaptive frameworks. Every career in project management has a beginning and that is the purpose of this course. You will learn the fundamentals of project management. This includes project performance, when to use the predictive or adaptive methodologies, business analysis domains, and frameworks, as well as the proper use of one of the various adaptive frameworks.

In this course, we will learn about the future's technology called WebRTC by building two real-world chat applications. We will learn what is WebRTC, why it is important, how it works, and cover the different protocols used in WebRTC. A basic understanding of HTML, CSS, and JavaScript is required.

Begin your machine learning journey by learning all about linear regression, logistic regression, and cluster analysis

Learn and master Excel 2019 by learning advanced functions and formulas

Implement machine learning-based clustering and classification in Python for pattern recognition and data analysis

Python Data Analytics with Python using Numpy, Pandas, Dataframes. Most attendees are in-work Data Professional. Private individuals are very welcome. Our Style: Hands-on, Practical Location: Online, Instructor-led

Learn to use DevOps tools from an industrial point of view. This course will help you get a firsthand experience of what it is like to be a DevOps engineer. Create DevOps CI/CD pipelines using Git, Jenkins, Ansible, Docker, SonarQube, and Kubernetes on AWS. Start your DevOps journey today. This course has been created from the perspective of a DevOps engineer who doesn't typically write application code.

Duration 5 Days 30 CPD hours This course is intended for Entry- to mid-level network engineers Network administrators Network support technicians Help desk technicians Overview After taking this training, you should be able to: Illustrate the hierarchical network design model and architecture using the access, distribution, and core layers Compare and contrast the various hardware and software switching mechanisms and operation while defining the Ternary Content Addressable Memory (TCAM) and Content Addressable Memory (CAM) along with process switching, fast switching, and Cisco Express Forwarding concepts Troubleshoot Layer 2 connectivity using VLANs and trunking Implement redundant switched networks using Spanning Tree Protocol Troubleshoot link aggregation using Etherchannel Describe the features, metrics, and path selection concepts of Enhanced Interior Gateway Routing Protocol (EIGRP) Implement and optimize Open Shortest Path First (OSPF)v2 and OSPFv3, including adjacencies, packet types and areas, summarization, and route filtering for IPv4 and IPv6 Implement External Border Gateway Protocol (EBGP) interdomain routing, path selection, and single and dual-homed networking Implement network redundancy using protocols such as Hot Standby Routing Protocol (HSRP) and Virtual Router Redundancy Protocol (VRRP) Implement internet connectivity within Enterprise using static and dynamic Network Address Translation (NAT) Describe the virtualization technology of servers, switches, and the various network devices and components Implement overlay technologies such as Virtual Routing and Forwarding (VRF), Generic Routing Encapsulation (GRE), VPN, and Location Identifier Separation Protocol (LISP) Describe the components and concepts of wireless networking, including Radio Frequency (RF) and antenna characteristics, and define the specific wireless standards Describe the various wireless deployment models available, including autonomous Access Point (AP) deployments and cloud-based designs within the centralized Cisco Wireless LAN Controller (WLC) architecture Describe wireless roaming and location services The Implementing and Operating Cisco Enterprise Network Core Technologies (ENCOR) v1.3 training gives you the knowledge and skills needed to install, configure, operate, and troubleshoot an enterprise network and introduces you to overlay network design by using SD-Access and SD-WAN solutions. You?ll also learn to understand and implement security principles and automation and programmability within an enterprise network. Course Outline Examining Cisco Enterprise Network Architecture Exploring Cisco Switching Paths Implementing Campus LAN Connectivity Building Redundant Switched Topology Implementing Layer 2 Port Aggregation Understanding EIGRP Implementing OSPF Optimizing OSPF Exploring EBGP Implementing Network Redundancy Implementing NAT Introducing Virtualization Protocols and Techniques Understanding Virtual Private Networks and Interfaces Understanding Wireless Principles Examining Wireless Deployment Options Understanding Wireless Roaming and Location Services Examining Wireless AP Operation Implementing Wireless Client Authentication Troubleshooting Wireless Client Connectivity Implementing Network Services Using Network Analysis Tools Implementing Infrastructure Security Implementing Secure Access Control Discovering the Basics of Python Programming Discovering Network Programmability Protocols Implementing Layer 2 Port Aggregation Discovering Multicast Protocols Understanding QoS Exploring Enterprise Network Security Architecture Exploring Automation and Assurance Using Cisco DNA Center Examining the Cisco SD-Access Solution Understanding the Working Principles of the Cisco SD-WAN Solution

Duration 5 Days 30 CPD hours This course is intended for This course is designed for business professionals who leverage data to address business issues. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming. However, there is not necessarily a single organizational role that this course targets. A prospective student might be a programmer looking to expand their knowledge of how to guide business decisions by collecting, wrangling, analyzing, and manipulating data through code; or a data analyst with a background in applied math and statistics who wants to take their skills to the next level; or any number of other data-driven situations. Ultimately, the target student is someone who wants to learn how to more effectively extract insights from their work and leverage that insight in addressing business issues, thereby bringing greater value to the business. Overview In this course, you will learn to: Use data science principles to address business issues. Apply the extract, transform, and load (ETL) process to prepare datasets. Use multiple techniques to analyze data and extract valuable insights. Design a machine learning approach to address business issues. Train, tune, and evaluate classification models. Train, tune, and evaluate regression and forecasting models. Train, tune, and evaluate clustering models. Finalize a data science project by presenting models to an audience, putting models into production, and monitoring model performance. For a business to thrive in our data-driven world, it must treat data as one of its most important assets. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, it can also inform?by guiding decisions and influencing day-to-day operations. This calls for a robust workforce of professionals who can analyze, understand, manipulate, and present data within an effective and repeatable process framework. In other words, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice Addressing Business Issues with Data Science Topic A: Initiate a Data Science Project Topic B: Formulate a Data Science Problem Extracting, Transforming, and Loading Data Topic A: Extract Data Topic B: Transform Data Topic C: Load Data Analyzing Data Topic A: Examine Data Topic B: Explore the Underlying Distribution of Data Topic C: Use Visualizations to Analyze Data Topic D: Preprocess Data Designing a Machine Learning Approach Topic A: Identify Machine Learning Concepts Topic B: Test a Hypothesis Developing Classification Models Topic A: Train and Tune Classification Models Topic B: Evaluate Classification Models Developing Regression Models Topic A: Train and Tune Regression Models Topic B: Evaluate Regression Models Developing Clustering Models Topic A: Train and Tune Clustering Models Topic B: Evaluate Clustering Models Finalizing a Data Science Project Topic A: Communicate Results to Stakeholders Topic B: Demonstrate Models in a Web App Topic C: Implement and Test Production Pipelines

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Developers responsible for developing Deep Learning applications Developers who want to understand concepts behind Deep Learning and how to implement a Deep Learning solution on AWS Overview This course is designed to teach you how to: Define machine learning (ML) and deep learning Identify the concepts in a deep learning ecosystem Use Amazon SageMaker and the MXNet programming framework for deep learning workloads Fit AWS solutions for deep learning deployments In this course, you?ll learn about AWS?s deep learning solutions, including scenarios where deep learning makes sense and how deep learning works. You?ll learn how to run deep learning models on the cloud using Amazon SageMaker and the MXNet framework. You?ll also learn to deploy your deep learning models using services like AWS Lambda while designing intelligent systems on AWS. Module 1: Machine learning overview A brief history of AI, ML, and DL The business importance of ML Common challenges in ML Different types of ML problems and tasks AI on AWS Module 2: Introduction to deep learning Introduction to DL The DL concepts A summary of how to train DL models on AWS Introduction to Amazon SageMaker Hands-on lab: Spinning up an Amazon SageMaker notebook instance and running a multi-layer perceptron neural network model Module 3: Introduction to Apache MXNet The motivation for and benefits of using MXNet and Gluon Important terms and APIs used in MXNet Convolutional neural networks (CNN) architecture Hands-on lab: Training a CNN on a CIFAR-10 dataset Module 4: ML and DL architectures on AWS AWS services for deploying DL models (AWS Lambda, AWS IoT Greengrass, Amazon ECS, AWS Elastic Beanstalk) Introduction to AWS AI services that are based on DL (Amazon Polly, Amazon Lex, Amazon Rekognition) Hands-on lab: Deploying a trained model for prediction on AWS Lambda Additional course details: Nexus Humans Deep Learning on AWS training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Deep Learning on AWS course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.